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2024 | OriginalPaper | Chapter

Using AI-Based Code Completion for Domain-Specific Languages

Authors : Christina Piereder, Günter Fleck, Verena Geist, Michael Moser, Josef Pichler

Published in: Product-Focused Software Process Improvement

Publisher: Springer Nature Switzerland

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Abstract

Code completion is a very important feature of modern integrated development environments. Research has been done for years to improve code completion systems for general-purpose languages. However, only little literature can be found for (AI-based) code completion for domain specific languages (DSLs). A DSL is a special-purpose programming language tailored for a specific application domain. In this paper, we investigate whether AI-based state-of-the-art code completion approaches can also be applied for DSLs. This is demonstrated using the domain-specific language TTI (Thermal Text Input). TTI is used for power transformer design specification in an industrial context, where an existing code completion shall be replaced by an advanced machine learning approach. For this purpose, implementations of two code completion systems are adapted to our needs. One of them shows very promising results and achieves a top-5 accuracy of 97%. To evaluate the practical applicability, the approach is integrated into an existing editor of a power transformer manufacturer.

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Title: Using AI-Based Code Completion for Domain-Specific Languages
Authors: Christina Piereder
Günter Fleck
Verena Geist
Michael Moser
Josef Pichler
Publisher: Springer Nature Switzerland
Book: Product-Focused Software Process Improvement
Print ISBN: 978-3-031-49265-5

Electronic ISBN: 978-3-031-49266-2

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-3-031-49266-2_16

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